Data platform and Bayesian forecasting of Swiss lakes – DATALAKES

Co-PIs:

  • Jonas Šukys (Eawag)
  • Damien Bouffard (Eawag)
  • Johny Wuest (EPFL)
  • Siddhartha Mishra (ETH Zürich)

Problem:

  • Increasing pressure on lakes needs scientific support
  • 3D numerical simulations of lakes require input data – uncertainty quantification in parameters & forecast
  • New L’EXPLORE platform in Lake Geneva – increasing availability of high resolution data

Solution:

  • Sensor-to-frontend open data platform
  • Physics-driven hydrodynamic models
  • Data-driven modeling of input data processes
  • Parallel Bayesian inference – MCMC with ABC or PF
  • Multi-level speedup – hierarchical numerical models

Impact:

  • Real time monitoring & future forecast of lakes
  • Platform for large-scale interdisciplinary collaborations
  • Research in hydrological / ecological lake modeling
  • Scientifically grounded water resources management